System, method, and computer program product for contact center management

ABSTRACT

A system, method, and computer program product for customer contact management via voice, chat, e-mail and social network contacts includes a balanced service process (BSP) that includes a plurality of cause or response codes for maximizing first contact resolution (FCR) and CSAT. The BSP is incorporated within a contact center (single center, multiple centers and/or work at home), which receives voice calls, SMS messages, email, chat, or social media communications from customers. The BSP in real-time determines dispositions of such contacts, monitors and manages the performance of individual resolvers.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of and claims the priority benefit ofco-pending U.S. patent application Ser. No. 14/487,544, filed Sep. 16,2014, which is a continuation-in-part of and claims the priority benefitof U.S. patent application Ser. No. 13/409,467, filed on Mar. 1, 2012,now U.S. Pat. No. 8,838,788, the entire contents of which areincorporated herein by reference, and which also claims the prioritybenefit of U.S. Provisional Patent Applications No. 61/538,405, filed onSep. 23, 2011 and No. 61/549,918, filed on Oct. 21, 2011, which are alsoincorporated herein by reference.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention in its disclosed embodiments is related generallyto the customer relationship management (CRM) process, and moreparticularly to a novel system, method, and computer program product forcustomer contact management that includes a balanced service process foraccurately measuring and maximizing first call or contact resolution(FCR) and customer satisfaction (CSAT) by aligning the company contactpoint's view or perception of disposition with customer view ofdisposition.

Statement of the Prior Art

Many market leaders build their brand strategy around customerexperience (CX). It has been found that the average large company gains$0.5B in annual revenue by becoming above average in CX relative to itspeers. While organizations set strategy around CX, their actions stillfocus on compliance and “check-the-box” activities. And, according toRyan Smith and Luke Williams in “The Most Common Reasons CustomerExperience Programs Fail,” Harvard Business Review (Dec. 28, 2016): “Dueto lack of agent embracement, an alarming 70 percent of all FCR andCustomer Experience initiatives fail to result in changes that customersnotice.”

It is a fact that customer surveys are the purest measure of customerexperience. It is also a fact that customer surveys are the key tocoaching agents and aligning contact points to improve CX. However, itis further a fact that on average, 85% of customers don't respond tosurveys. Moreover, on average, only 25% of survey respondents aredissatisfied. The resulting problem is that out of 100 surveysolicitations, only about three are useful for coaching.

One approach to solving this problem is to provide customer engagementcenters (CEC), which are comprehensive systems for multi-channelcustomer service and support. This type of office and system assistsbusinesses in making sure that customer interactions are consistent andeffective. One thing that a CEC might do is to gather information fromdifferent portals or channels, including various social media platforms,and provide protocols for dealing with customers on the phone or indigital environments.

IT professionals design sets of business process technologies to figureout how best to interact with customers in any given situation. Thesesystems are often built on top of simple call center operations to helpguide each individual worker's interactions with customers. For example,with better current information about the customer, company contacts cansay the right things and generally satisfy the customer's needs, whileappearing more intelligent about the customer's relationship with thebusiness. Many CECs offer features like: real-time analytics;mobile-enabled platforms; peer-to-peer support; and integration withcompany telephony.

Because customer service is so critically important to businesses, a CECcan be a good investment in making sure that things are done right everytime a company interacts with their customer, no matter how theseinteractions take place.

As seen in FIG. 1, Gartner's Magic Quadrant® for customer engagementcenters is shown as of May 2017. A Magic Quadrant provides a graphicalcompetitive positioning of four types of technology providers, inmarkets where growth is high and provider differentiation is distinct.Leaders (e.g., Salesforce) execute well against their current vision andare well positioned for tomorrow. Visionaries understand where themarket is going or have a vision for changing market rules, but do notyet execute well. Niche Players focus successfully on a small segment,or are unfocused and do not out-innovate or outperform others.Challengers execute well today or may dominate a large segment, but donot demonstrate an understanding of market direction.

While these approaches can certainly reduce costs, they also can reducecustomer satisfaction and loyalty. A better way to approach the issue isto put more focus on taking care of the customer's issue during thefirst contact. Improving first call or contact resolution (FCR) not onlyimpacts the cost of operations, but also simultaneously affects customersatisfaction and retention. By improving FCR and reducing the totalvolume of repeat calls, companies can significantly lower service timeand the overall cost to serve the customer. From a customer'sperspective, improved FCR translates directly to higher satisfactionwhich further impacts the bottom line by boosting customer loyalty andrevenues. As a matter of fact, having the issue resolved on the firstcontact has been cited in many studies as being the number one driver ofcustomer satisfaction.

The pursuit of increasing FCR rates is the idealistic goal of anyorganization reliant upon contact center support. However, mountains ofdata, armies of analysts and management's ever-changing reaction to FCRcrises often leave both customer management staff and company leadershipapathetic and unable to serve the customer. This leaves customersfrustrated and often drives them away. At the core of the problem is aninsufficient or nonexistent set of tools to confront the challenge andthe lack of a detailed process dedicated to rectifying the situation, asa result: (a) confusing and ever-changing processes are implemented; (b)staff morale is unfavorably impacted, decreasing tenure and increasingattrition; and (c) customers are lost.

SUMMARY OF THE INVENTION

Accordingly, it is generally an object of certain embodiments of thepresent invention to provide a system, method, and computer programproduct to accurately measure and manage first contact resolution (FCR)and customer satisfaction (CSAT) at an actionable (i.e., from agent tocustomer) level.

More specifically, it is an object of those and other embodiments of thepresent invention to generate per-call data in real-time that accuratelyrepresents the customer's perception and opinion.

The above and other objects are provided by the balanced service processdescribed herein, which provides (a) accurate real-time, intraday, andhistorical FCR and CSAT statistics; (b) dynamic reporting of issuesdriving call volume and customer experience; (c) analysis of contactsthat were not resolved; (d) a closed loop channel to define, report andcorrect trending issues that impede FCR and CSAT; and (e) a customercontact point and customer calibrator which closely aligns an contactspoint's perception of disposition with a customer's perception ofdisposition.

Through the implementation of the balanced service process, the system,method, and computer program product according to embodiments of thepresent invention will demonstrate, with empirical data, the followingbenefits: (a) lower operating expense; (b) reduced service relatedcontacts; and (c) improved customer satisfaction.

Further objects, advantages, and novel features of the embodiments ofthe present invention and the structure and operation thereof, aredescribed in detail below with reference to the accompanying drawings,wherein:

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts the Gartner Magic Quadrant® for customer engagementcenters;

FIG. 2 depicts a high-level block diagram of a system for customerrelationship management according to embodiments of the presentinvention;

FIG. 3 depicts the balanced service process according to an embodimentof the present invention;

FIG. 4 depicts a flowchart for maximizing first contact resolutionaccording to one embodiment of the present invention;

FIGS. 5A and 5B depict a balanced service process according to anotherembodiment of the present invention for responding to an email contact;

FIG. 6 depicts a balanced service process according to anotherembodiment of the present invention for responding to a phone call;

FIGS. 7A and 7B depict a balanced service process according to anotherembodiment of the present invention for responding to a chat contact;

FIG. 8 depicts a balanced service process according to anotherembodiment of the present invention for use with calibrated agentpredictions;

FIG. 9 depicts a balanced service process according to anotherembodiment of the present invention for use with calibrated agentpredictions;

FIG. 10 depicts a balanced service process according to anotherembodiment of the present invention including machine learning;

FIG. 11 depicts a calibration dashboard for use with the balancedservice process according to an embodiment of the present invention;

FIG. 12 depicts another calibration dashboard for use with the balancedservice process according to an embodiment of the present invention;

FIG. 13 depicts an executive dashboard for use with the balanced serviceprocess according to an embodiment of the present invention;

FIG. 14 depicts another executive dashboard for use with the balancedservice process according to an embodiment of the present invention; and

FIG. 15 depicts a Zacoustic Predictive Survey form according to anembodiment of the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Exemplary embodiments are discussed in detail below. While specificexemplary embodiments are discussed, it should be understood that thisis done for illustration purposes only. In describing and illustratingthe exemplary embodiments, specific terminology and contact types areemployed for the sake of clarity. However, the embodiments are notintended to be limited to the specific terminology and contact types soselected. Persons of ordinary skill in the relevant art will recognizethat other components and configurations may be used without departingfrom the true spirit and scope of the embodiments. It is to beunderstood that each specific element includes all technical equivalentsthat operate in a similar manner to accomplish a similar purpose. Theexamples and embodiments described herein are non-limiting examples.

Embodiments of the present invention may include apparatuses and/orcontact types for performing the operations disclosed herein. Anapparatus may be specially constructed for the desired purposes, or itmay comprise a general-purpose device selectively activated orreconfigured by a program stored in the device.

Embodiments of the invention may also be implemented in one or acombination of hardware, firmware, and software. They may be implementedas instructions stored on a machine-readable medium, which may be readand executed by a computing platform to perform the operations describedherein. A machine-readable medium may include any mechanism for storingor transmitting information in a form readable by a machine (e.g., acomputer). For example, a machine-readable medium may include read onlymemory (ROM); random access memory (RAM); magnetic disk storage media;optical storage media; flash memory devices; and others.

In the following description and claims, the terms “computer programmedium” and “computer readable medium” may be used to generally refer tomedia such as, but not limited to removable storage drives, a hard diskinstalled in hard disk drive, and the like, etc. These computer programproducts may provide software to a computer system. Embodiments of theinvention may be directed to such computer program products.

References to “one embodiment,” “an embodiment,” “example embodiment,”“various embodiments,” etc., may indicate that the embodiment(s) of theinvention so described may include a particular feature, structure, orcharacteristic, but not every embodiment necessarily includes theparticular feature, structure, or characteristic. Further, repeated useof the phrase “in one embodiment,” or “in an exemplary embodiment,” donot necessarily refer to the same embodiment, although they may.

In the following description and claims, the terms “coupled” and“connected,” along with their derivatives, may be used. It should beunderstood that these terms are not intended as synonyms for each other.Rather, in particular embodiments, “connected” may be used to indicatethat two or more elements are in direct physical or electrical contactwith each other. “Coupled” may mean that two or more elements are indirect physical or electrical contact. However, “coupled” may also meanthat two or more elements are not in direct contact with each other, butyet still cooperate or interact with each other.

An algorithm is here, and generally, considered to be a self-consistentsequence of acts or operations leading to a desired result. Theseinclude physical manipulations of physical quantities. Usually, thoughnot necessarily, these quantities take the form of electrical ormagnetic signals capable of being stored, transferred, combined,compared, and otherwise manipulated. It has proven convenient at times,principally for reasons of common usage, to refer to these signals asbits, values, elements, symbols, characters, terms, numbers or the like.It should be understood, however, that all of these and similar termsare to be associated with the appropriate physical quantities and aremerely convenient labels applied to these quantities.

Unless specifically stated otherwise, and as may be apparent from thefollowing description and claims, it should be appreciated thatthroughout the specification descriptions utilizing terms such as“processing,” “computing,” “calculating,” “determining,” or the like,refer to the action and/or processes of a computer or computing system,or similar electronic computing device, that manipulate and/or transformdata represented as physical, such as electronic, quantities within thecomputing system's registers and/or memories into other data similarlyrepresented as physical quantities within the computing system'smemories, registers or other such information storage, transmission ordisplay devices.

In a similar manner, the term “processor” may refer to any device orportion of a device that processes electronic data from registers and/ormemory to transform that electronic data into other electronic data thatmay be stored in registers and/or memory. A “computing platform” maycomprise one or more processors.

Embodiments of the present invention may further include apparatusesand/or manual systems for performing the operations described herein. Anapparatus or system may be specially constructed for the desiredpurposes, or it may comprise a general-purpose device selectivelyactivated or reconfigured by a program stored in the device.

FCR as used herein can refer to first call resolution or first contactresolution, because a contact within the embodiments of the presentinvention may refer to any one or more of the following: face-to-faceinteractions, voice calls, SMS messages, email, chat, or social mediacommunications from customers.

Systems according to embodiments of the present invention may generateFCR, CSAT and Response Codes—issues that are driving call volume—data,all in actionable or real-time. The data, when analyzed, creates actionplans to address process, behavioral, and recurrent training problemsand also serves as the basis for an agent's reward and recognitionprogram.

FCR is inarguably the most important metric in the contact centerenvironment, simultaneously driving and addressing customersatisfaction, quality and efficiency. Response Codes allow for tacticalintraday, and strategic long-term, management of the top issues drivingcustomer contacts. It should be noted at this juncture that “ResponseCodes” may also be referred to herein as cause drivers, interactiondrivers, or key performance indicators.

Fundamentally, the BSP relies on “customer contact points” (contactcenter agents, BOTs, etc.) to generate FCR and CSAT data. At the end ofevery contact the customer contact point must disposition each contactbefore another is presented: “YES” if the issue was resolved and “NO” ifthe issue was not resolved. Low “exception rates” (i.e., where there aredifferent Agent and customer dispositions for the same record) and high“resolution rates” (i.e., where the Agent and customer both dispositionthe record as “YES”) is the goal. Low exception rates and low resolutionrates suggest training is required. High exception rates and lowresolution rates indicate a process or policy breakdown, and highexception rates with high resolution rates suggest Agent behaviorissues.

The accuracy of the BSP can be measured by the level of alignment withthe customers' perception of resolution and satisfaction. If thecustomer and the Agent are in synchronicity with regard to theperception of both, and assuming all policies were adhered to, thecontact may be declared resolved and accurately measured with greatconfidence. Conversely, when there is a divergence in the perception ofresolution between the Agent and customer, there are valuable process,training, and Agent behavior management opportunities. When the processis applied, resolution and CSAT barriers quickly emerge and targetedactions can be initiated.

Portions of some processes similar to the BSP may have been deployed inother contact centers. However, without deployment of the processespresent in the BSP, the reliability of data and the ability toconsistently execute an FCR and CSAT strategy is not possible.Short-term FCR and CSAT “campaigns” often reduce frontline employees toapathy and fear, and create ongoing client stress. Survey results can“indicate” opportunities for improvement, but are of little value overthe long run unless they are integrated at the operational level andused for ongoing management of the business. BSP makes FCR and CSAT anintraday-managed metric, analogous to service level or handle time.Moreover, there is human behavior at play. When an Agent knows thathe/she must accurately disposition each record before proceeding to thenext contact, and will be evaluated primarily on the outcome, a cultureof resolution is institutionalized enterprise wide. Without the BSPconcerns related to accuracy and a built-in bias at the Agent level arejustified; however, the BSP ties each Agent and customer's dispositionstogether via a simple survey, asking the same two questions: “Was theissue resolved?” “Was the customer satisfied with the service?” Thiscounterbalance allows patterns in synchronicity between the Agent andthe customer's perception to emerge, and actions to be created toaddress the gaps.

Obviously, customers are more concerned with issue resolution thancontact resolution. The contact is just the means to the end, in thecustomer's perception. Recognizing this, the customer IVR surveystrategy that the system, method, and computer program product executesis sensitized to the type of issue that was reported. For example, ifthe contact was a billing concern, the customer may be surveyed afterthey have received the next bill to determine FCR rather thanimmediately, post-contact. In this example, the customer may think theirissue has been resolved but doesn't really know for sure until thecorrection is observed on the next bill. In an environment where theAgent has the tools to resolve the issues upon first contact,post-contact surveys are deployed. Either way, milestones must bedecided upon and used if necessary as triggers for customer surveys toensure the accuracy of data.

Analytics may also be used to generate an automated Response Code. Suchanalytics may comprise voice analytics or video analytics, which producean automated cause or response code for each contact, and presents themin real-time and historically. These cause or response codes may itemizethe combination of agent and customer survey responses, and mayculminate in performance management software known as Zacoustic™ (anapplication monitor and network performance monitoring and managementtool), and they are presented in descending order within a real-timedashboard. Material increases in individual cause or response codesgenerate an alert, informing management that a particular “on-the-rise”issue may be of concern and may require intervention, lest FCR rates areimpeded.

Zacoustic may also generate exceptions (which are defined as variancesin responses between the Agent and the customer), which are thenreviewed by a Quality Assurance (QA) team. With 100% contact recording,the QA analyst/supervisor reviews contacts and makes the determinationas to whether exceptions are rooted in process, skill or behavior. Astrends develop, targeted action plans are created and executed upon.

As processes are progressively fixed and training and behavior issuesare addressed, FCR and satisfaction rates increase. Measures to ensureAgent performance is consistently at or above standard are applied asindividual Agents work through learning curves or remediation.

Referring now to the drawings, wherein like reference numerals andcharacters represent like or corresponding parts and steps throughouteach of the many views, there is shown in FIG. 2 a high-level blockdiagram of a system 200 for customer relationship management accordingto embodiments of the present invention. System 200 generally comprisesa contact center (which may comprise, e.g., single or multiple locationsand/or work at home in the form of a call center or a customerengagement center) 202, which may include an Automatic Call Distributor(ACD) 204, Computer Telephony Integration (CTI) hardware/software 206,the Balanced Service Processor (Zacoustic) 208, Interactive VoiceResponse (IVR) hardware/software 212, and a database 216. IVR 212 mayfurther comprise a chat BOT 214, while Zacoustic 208 may be coupled to aBOT (AI) 210 and a database 218.

As is known, ACD 204 may suitably comprise a device or system thatdistributes incoming calls to a specific group of terminals that agents(i.e., Agents 210, 214, 228 or supervisors/monitors 232) use. It isoften part of a CTI system. Routing incoming calls is the task of theACD 204. ACD systems are often found in offices that handle largevolumes of incoming phone calls from callers who have no need to talk toa specific person but who require assistance from any of multiplepersons (e.g., customer service representatives) at the earliestopportunity. The system consists of hardware for the terminals andswitches, phone lines, and software for the routing strategy. Therouting strategy is a rule-based set of instructions that tells the ACD204 how calls are handled inside the system. Typically, this is analgorithm that determines the best available employee or employees torespond to a given incoming call. To help make this match, additionaldata may be solicited and reviewed to find out why the customer iscalling. Sometimes the caller's caller ID or ANI, or the dialed number(DNIS) may be used. More often, a simple interactive voice response suchas may be used with IVR 212 is used to ascertain the reason for thecall.

Alternatively, ACD 204 may suitably comprise an Internet call managementdevice of the types described in U.S. Pat. No. 8,005,024, entitled“Method For Establishing An IP Video-Conference Using A TelephoneNetwork For Voice Transmission,” U.S. Pat. No. 6,819,667, entitledPSTN-Internet Notification Services,” and U.S. Pat. No. 6,404,860,entitled “System And Method For Internet Call Management WithText-To-Speech Messaging,” each of which is incorporated herein byreference.

CTI 206 may be used for other functions such as screen pops; callinformation display (ANI/DNIS); dialing (e.g., power dial, preview dial,and predictive dial; phone control in general and more particularly callcontrol and feature control; transfers; advanced call reportingfunctions, etc.).

System 200 is connected to receive calls from a PSTN 220 and IP network222. As is known, the PSTN 220 is the network of the world's publiccircuit-switched telephone networks, in much the same way that theInternet is the network of the world's public IP-based packet-switchednetworks (conceptually shown in FIG. 2 as IP network 222). Originally anetwork of fixed-line analog telephone systems, the PSTN 220 is nowalmost entirely digital, and now includes mobile as well as fixedtelephones. It is sometimes referred to as the Plain Old TelephoneService (POTS).

Phones used to access the system 200 may be conventional wirelinephones, wireless phones, IP phones, satellite phones, and the like. Asis known, use of the phones by users may provide certaintelecommunications features such as Automatic Number Identification(ANI) and Dialed Number Identification Service (DNIS). ANI provides thephone call recipient with the caller's phone number. The technology andmethod used to provide this information is determined by the serviceprovider, and is often provided by sending DTMF (i.e., digital tonemulti frequency) tones along with the call.

Also known as Automated Number Identification or Calling LineIdentification (CLI), ANI may arrive over the D channel of an ISDN PRIcircuit (out-of-band signaling), or before the first ring on a singleline (in band signaling). Caller ID is the local phone company versionof ANI, and is usually delivered in band.

In contact center applications, ANI displays the number of the caller tothe phone representative or Agent in real-time. Among other things, thecontact center can use the information to process the call based uponprior history or can forward the call to a different department ororganization.

DNIS is a service sold by telecommunications companies to corporateclients that lets them determine which telephone number was dialed by acustomer. This is useful in determining how to answer an inbound call.The telecommunications company sends a DNIS number to the client phonesystem during the call setup. The DNIS number is typically 4 to 10digits in length.

For example, a company may have a different toll-free number for eachproduct line it sells. If a contact center is handling calls formultiple product lines, the switch that receives the call can examinethe DNIS, and then play the appropriate recorded greeting. Anotherexample of multiple toll-free numbers might be used for multi-lingualidentification. A dedicated toll-free number might be set up for Spanishspeaking customers.

With IVR (i.e., interactive voice response) systems, DNIS may be used asrouting information for dispatching purposes, to determine which scriptor service should be played based on the number that was dialed to reachthe IVR platform. For example, 0906 123 4567 and 0906 123 4568 may wellboth connect to the same IVR system, but one number may be required toprovide a competition service and the other might be an informationline. The DNIS is what distinguishes these lines from each other andhence the IVR will know which service to provide to the caller.

A phone call, chat, or email may come into the contact center 202through the PSTN 220 or IP network 222 or other computer connection. Itmay be processed through a router/gateway 224 and switch 226 to thecontact center 202. The contact center 202, in turn, may decide whichagent/Agent 228 BOT 210 or Chat BOT 214 gets the contact and performsthe Zacoustic process ( ) according to embodiments of the presentinvention described herein.

Zacoustic 208 may consist of the following successive components. DataGeneration is the first step, in which the Agent disposition of contact(RDP), customer disposition of contact (CDP), and FCR calculation aredetermined. A cause or response code may be manually determined orautomatically generated by use of voice or video analytics. QualityAssurance (QA) is then used to determine exceptions, and monitoring/callreview. The exceptions may then be analyzed.

As defined above, the steps of Zacoustic 208 may include an “actionplan,” which sets forth the actions stemming from trends in exceptionanalysis related to (a) process; (b) training; and (c) behavior. An“application cause” is the primary reason the customer contacted thecontact center 202 as displaced in the client's application. “BehaviorReconditioning” may comprise the actions stemming from data thatilluminates Agent behavior (e.g., deliberate miscoding of dispositions)that requires some or all of; coaching, counseling, termination, andwhen completed, increases data accuracy and FCR rates.

Resolved rate or “Billable Resolution Rate” comprises a metric that canbe used to account for cost of bill the client for resolved contactsonly. It may be calculated as follows: TOTAL “YES” RDP+TOTAL “OUT OFCONTROL” RDPs (as determined by QA).

A “contact” may comprise the act of a customer contacting the contactcenter 202 (i.e., phone, chat, e-mail). Alternatively, a “contact” maycomprise customer queries via social media. The ability to effectivelydeal with such customer queries requires companies to have in place someform of system to monitor what is being said about the company acrossvarious social media channels, including blogs, Twitter and LinkedIn.Dozens of such services exist to help, feeding companies all sorts ofinformation on what is being said about them, based on whatever keywords they select.

A growing number of companies are now trying to manage thosetransactions, so they come in to a contact center queue just like aphone call does. Zacoustic 208 may also queue such interactions, deliverthem to appropriately skilled agents/Agents 228, BOT's 210 and ChatBOT's 214 and monitor the response and report on the outcomes. Zacoustic208 may even keep track of which contact point handles each interaction,in case any follow-up is required.

A “Cause of Contact” may comprise the primary reason for the customercontacting the contact center 202. It may be derived and digitallyconverted to a cause or response code (collectively referred to as“Response Code”) and sent to Zacoustic (a customer experience managementsystem for contact centers available from BalanceCXl, Inc. of Austin,Tex. USA) via voice or video analytics.

A “Response Code” may comprise the coding that resides in Zacousticrelated to the Cause of Contact that may be digitally derived via VoiceAnalytics.

A “CDP” (or Customer Disposition) may comprise the record of thecustomer's response to the IVR survey (e.g., “Was the issue resolved?”).The QA (or Quality Assurance) team analyzes exceptions and determinesroot cause, broken into three major components, (a) process; (b)training; and (c) behavior. Data may comprise the total numbers of “YES”and “NO” dispositions, which are generated by Agents and customers andis used for operations, decision-making and planning.

A “Disposition” may comprise responses to surveys which ask Agents andcustomers “Was the issue resolved?” It is mandatory that the Agentrespond at the end of each contact, via Zacoustic. The customers aregiven the option of post call—and post any milestones—via IVR survey.Responses are either “YES” (i.e., the issue was resolved/customer wassatisfied) or “NO” (i.e., the issue was not resolved/customer was notsatisfied). Responses become data. An “Exception” may comprise adifferent disposition/response for the same record(s) as dispositionedby the Agent and the customer.

An “Exception Analysis” may comprise the determination made by QAregarding the root cause of the Exception. Among such root causes are:(a) client process; (b) CRM process; (c) Agent training; and (d) Agentbehavior. The “Exception Rate” may comprise the percentage of variancesin responses between the customer and the Agent (calculated as TOTALEXCEPTIONS/TOTAL CDP's).

“Milestones” may comprise the events that trigger the initiation ofcustomer surveys (e.g., billing dates, return dates, etc.). Surveys mustbe tied to milestones to ensure that the customer's perception ofresolution is accurate.

“Process Reconditioning” may comprise actions stemming from data thatilluminates a process, either on behalf of the BPO or client thatrequires repair and when completed, should increase FCR.

“Recurrent Training” may comprise actions stemming from data thatilluminates a need for refresher training for one, some or all Agentswho support a certain product, service, or process, when completed,should increase FCR.

“Resolution Rate” may comprise the percentage of contacts that theprovider resolves calculated as (RDP “YES”/TOTAL CALLS HANDLED).

Zacoustic (i.e., the performance management software which powers thebalanced service process) supports and runs on BSP 208, and displays keyperformance metrics in real-time, including—and most importantly—FCRstatistics and CSAT. Zacoustic resides on every Agent's, supervisor's,and client's desktop 230, 234, providing the necessary feedback requiredoptimizing intraday FCR performance. Its primary function is tocalculate customer satisfaction and call resolution metrics, withvarious associations to those metrics, into certain formats and reports.

According to one embodiment of the present invention, such performancemanagement software is a cloud-based program developed in Java, withHTML providing an easily navigable graphical user interface. It wasdeveloped to provide open access from any platform running mostavailable browsers, including the following, or newer, browser releases:Google Chrome 24.0.1312.56; Firefox 18.0; Microsoft Internet Explorer9.0; and Safari 6.0. MySQL may be used to power the performancemanagement software in database 230. It may be built on a scalable,load-balance robust platform (e.g., GlassFish 3.0 servers) of the typethat is deployable through the cloud worldwide.

At the end of each contact, the Agent is presented with twoquestion(s), 1) “Was this issue resolved?” 2) Was the customer satisfiedwith the service received? The Agent must then select one of two radiobuttons, “YES” or “NO”. The response is sent to Zacoustic database 218where it will await CDP or QA analysis.

The FCR Rate and CSAT rate are immediately populated in Zacousticdatabase 218 along with the number of contacts the agent/enterprise hashandled within the same time period. Contacts handled data is generatedfrom the ACD 204. The FCR rate for individual Agents, supervisors,operations managers, accounts, clients and enterprise is then generated.The calculation for FCR rate is as follows: TOTAL “YES” RDP/TOTALCONTACTS HANDLED. The point in time in which a customer commitment hasbeen accomplished, should be inserted into the IVR decision tree andtriggered at the appropriate time, if required.

An IVR contact may be generated to the customer, post any milestonerequirements, and the customer is asked by the IVR, “You recentlycontacted [CLIENT] for [RESPONSE CODE], was this issue resolved? Press 1for “YES” and 2 for “NO” and “Were you satisfied with the serviceprovided by ______” Press 1 for “YES” and 2 for “NO”. IP networkcontacts are handled the same and made over the appropriate media.

The Exception Rate may be calculated as the total number of Exceptionsdivided by the total number of CDP's—the Exception Rate percentage isthen multiplied by the Resolution Rate and subtracted from theResolution Rate to give the billable Resolution Rate.

Voice and/or video analytics may be used to determine whether key wordsand phrases are identified and used to produce “Response Codes”, themain reason why a customer contacted the BPO/contact center 202. Oncegenerated, Response Codes are sent to Zacoustic where they are stackranked and presented on the main dashboard in descending order.

Changes in contact patterns can be quickly identified and immediatelyaddressed through the presentation of Response Codes in Zacoustic. Iftrends change dramatically, an alert is sent to the BPO/contact center205 and the client's management and the Response Code that is spikingcan be examined through live monitoring. Additionally, FCR Rates for theResponse Code in question may be produced and if the FCR Rate is low forthe Response Code in question

n, a material process or training issue is quickly identified and can beaddressed swiftly, thereby preserving FCR Rates.

When the Agent and the customer generate different dispositions for thesame contact, it is defined as an Exception. An Exception report, whichconsists of: (a) the RDP; (b) CDP; and (c) contact recording may bebundled and presented to the QA team. QA analysts review every exceptionto determine the root cause of the Exception. The three categories ofException root cause are process, training and behavior. The followingare examples for each:

Example 1

Process: Assume that a customer contacted the BPO/contact center 202 tohave an erroneous charge removed from their bill. The Agent followsprocedure and orders the charge removed, and dispositions the contact as“YES”. Due to an internal process error at the client, the charge is notremoved and when the customer is contacted, the CDP returns as “NO”.This creates an Exception and is routed to QA for further review. The QAanalyst determines that this is a process error on the client's side andconfirms the Agent followed procedure. As trends develop, it isestablished that 12% of all contacts are related to this same ResponseCode. This information is relayed back to the client via a “ProcessReconditioning Request”. Once the process is reconditioned, the FCR rateis favorably impacted for 12% of all contacts.

Example 2

Training: The client releases a new product and prior to release,training is conducted for all Agents. The training includes instructionson how to install the product and Agents execute to plan. However, aglitch in the system occurs moments after install disabling the productand all that was required was the install of a driver to remedy theissue. Upon completion of the contact the Agent dispositions the recordas “YES” and when surveyed the customer disposition is “NO”. Thiscreates an Exception and is routed to QA for further review. The QAanalyst coordinates with the client and determines that this is atraining error on the client's side and confirms the Agent followedprocedure. As trends develop it is established that 15% of all contactsare related to this same Response Code. This information is relayed backto the BPO/contact center 205 training via a “Training ReconditioningRequest”. Once the Agents receive recurrent training, the FCR rate isfavorably impacted for 15% of all contacts.

Example 3

Behavior: The BPO/contact center 205 may reward Agents with a highresolution rate and an individual Agent is close to being reward. He isnear his lunch break and he rushes a call to check out on time. Hedispositions the contact as “YES” and when surveyed, the customerdispositions the contact as “NO”. This creates an Exception and isrouted to QA for further review. The QA analyst determines that this isa behavior error. This information is relayed back to the Agent'ssupervisor 232 via a “Behavior Reconditioning Request”. The supervisor232 has three hours to meet with the Agent 228, review the call andinitiate counseling, which is stored progressively in Zacoustic database218. The Agent is now on notice and any further infractions of policyresult in progressive counseling up to and including termination ofemployment.

Significant sampling of contacts that lack CDP data are randomlyreviewed by QA and blindly—meaning the QA analyst cannot view either theRDP or CDP—and the QA analyst produces a disposition upon completion ofreview. If a (shadow) Exception is generated as a result of thisexercise, Exception Analysis as described herein below is conducted.

Significant samples of Exceptions are reviewed and the QA analyst makesa determination as whether the root cause of the Exception was (a) a CRMor client policy/process issue, (b) a training issue, meaning the Agentobviously lacked the tools or training needed to resolve the contact, or(c) a behavior issue, meaning it appears that the Agent deliberately andwrongfully dispositioned the contact.

The following actions stem from the various combinations RDP and CDP asshown in Table 1 below.

TABLE 1 Dispositions RDP CDP Likely Implication Action Item Yes Yes GoodPerformance Reward Yes No Agent Behavior Coach No Yes Process BreakdownClient interface to address process fix No No Training RequiredEstablish trends, develop and execute on training

As Exception analyses are produced, trends are analyzed and stack rankedin descending order. In the event that a CRM process is impeding FCR,and can be adjusted within the realm of fair practice, client approvalmay be sought, if required, and the process is adjusted. If Agenttraining is required to effect the process change, it is scheduled andexecuted upon as quickly as possible.

Both CRM and client process/policy reconditioning action items may betracked from the time a need was identified to the time the process orpolicy is fixed. Analysis that illustrates the impact of the brokenprocess can be produced using the following calculation: TOTAL BROKENPROCESS CONTACTS/TOTAL CONTACTS HANDLED. The percentage of thiscalculation may be removed from the overall FCR rate to clearlyillustrate the impact of the broken process thereby creating a crystalclear, tangible sense of urgency.

Agents who have ongoing high Resolution Rates, coupled with lowException Rates, may be recognized and rewarded in conjunction with anestablished program. Given the complexity of various scopes of work,reward and recognition programs may be developed on a program-by-programbasis.

Agents who demonstrate chronically low Resolution Rates and highException Rates may be placed on probationary counseling. If it isdetermined that the barrier for improvement is rooted in “will”, ratherthan “skill”, termination of employment should occur upon a prescribedfair HR practice.

As Exceptions statistics are analyzed using Zacoustic reporting tools,common trends in unresolved Response Codes quickly emerge. Thisinformation may be organized by: (a) frequency in Response Code; and (b)Exception Rates in descending order. The most frequent Response Codescoupled with the highest Exception Rates allows for targeted training.

The BPO and client should budget approximately 2 hours per Agent perweek for recurrent training. This training might be for an individualAgent or a group of Agents.

As data is collected for the client, the client/BPO may establish anormal learning curve period for the group of Agents assigned to theaccount. This learning curve will allow the CRM group to identify andcorrect performance and behavior trends as early as possible, whilegiving Agents the appropriate amount of time to learn the client'sbusiness.

Cause or response codes may be four-letter acronyms that itemize thecombination of agent and customer survey responses. Response codes maybe used to prioritize records for evaluation and for quickinterpretation among users of the balance process and Zacousticsoftware. In such a manner, they may categorize the combination of agentand customer survey responses while at the same time may be assigned apriority used for evaluation of the Agent Survey.

Such cause or response codes serve as a means to quickly describeagent-customer survey response alignment, the survey question respondedto (i.e., either satisfaction or resolution) and whether or not thecall-in question was a repeat. Response codes are generated only afterthe agent has responded to the Agent Survey and the customer hasresponded to the Customer Survey, or had the opportunity to respond anddid not.

Each Response Code may be assigned a level of priority and used withinan algorithm to help determine which Agent Surveys are to be evaluatedby Quality Assurance. Response Codes may appear in various screens andreports inside the application, allowing users to isolate agent-customeralignment concerns. An exemplary syntax of the Response Codes accordingto an embodiment of the present invention is described in Tables 2 and 3below.

TABLE 2 Response Code Letter Categories LETTER 1 2 3 4 CATEGORY SurveyQuestion Survey Agent Survey Repeat (Satisfaction or Alignment ResponseStatus Resolution)

TABLE 3 Response Code Categories LETTER 1 LETTER 2 LETTER 3 LETTER 4Survey Survey Agent Repeat Question Alignment Response Status SSatisfaction M Matching Y Yes F First R Resolution X Not Matching N No ZRepeat E Satisfaction A Agent-Only w/Milestone O Resolution w/Milestone

In addition to the above Response Code Categories, the system mayinclude Response Codes for instances with no Agent or Customer Surveyresponses, including Transfers, Dropped Contacts, Escalations, andFlagged Contacts as shown, for example, in Table 4 below. These specialResponse Codes may also be prioritized for QA review along with thestandard codes.

TABLE 4 Flagged, Dropped and Transferred Codes DISPOSITION DESCRIPTIONFlag Record Agents check the “Flag Record” box when it would beinappropriate for the customer to receive a survey For example, if thecustomer threatened legal action When the “Flag Record” box is checked,the rest of the survey questions, except the “Was this a repeatcontact?” become unavailable to the agent The “No” box for both, “Willthe customer tell us they were satisfied?” and “Will the customer tellus their issue was resolved?” questions are auto-populated 100% of theserecords are reviewed by the Data Assurance team Call Dropped Whenthrough no fault of the agent the call is terminated the call droppedfunction is utilized (e.g., technical issues or the customer hangs up)The importance of ensuring a one-to-one ratio of customer contacts toAgent Survey is of critical importance to the overall integrity of theBalanced Service Process and the data it produces Once the “Submit”button is pressed, the record becomes coded as a Call Dropped 100% ofCall Dropped records are reviewed by the Data Assurance team to ensurethat the disconnect was legitimate Call Transferred Calls that aretransferred are accounted for when the agent checks the “CallTransferred” box Once checked, all other fields in the Agent Survey arerendered unavailable The customer does not receive a survey when a callis transferred - only when the last agent who touches the customercontact completes the Agent Survey will the customer receive a surveyThe Data Assurance team reviews 100% of Call Transferred records tovalidate that the transfer was required

Response code creation may occur when the original agent responses areeither matched with a customer response or the window of opportunity forthe customer response closes. the window timeframe is set by the systemadministrator as part of the control panel functions for the software.

Response Codes may be separated into three clusters: (1) negative, (2)neutral, and (3) positive. Such clustering of response codes providesthe following benefits: grouping data; identifying trends; and anelement of quality assurance evaluation algorithms Exemplary ResponseCode clusters according to an embodiment of the present invention aredescribed in Table 5 below.

TABLE 5 Response Code Clusters CATEGORY CLUSTERS DESCRIPTION NegativeSat_Neg Groups satisfaction or resolution Response Codes wherein eitheror both the Res_Neg agent and the customer responded “No” to therespective survey question Neutral Sat_Neu Groups satisfaction orresolution Response Codes that cannot be definitively Res_Neucategorized as either negative or positive Positive Sat_Pos Groupssatisfaction or resolution Response Codes wherein both the agent andRes_Pos the customer responded “Yes” to the respective survey question

Response Codes may be defined as follows in Table 6 below.

TABLE 6 Response Codes CODE SURVEY ALIGNMENT AGENT CUST REPEAT CLUSTEREANF Satisfaction (w/Milestone) Agent-Only No N/A First Sat_Neg EANZSatisfaction (w/Milestone) Agent-Only No N/A Repeat Sat_Neg EAYFSatisfaction (w/Milestone) Agent-Only Yes N/A First Sat_Neu EAYZSatisfaction (w/Milestone) Agent-Only Yes N/A Repeat Sat_Neu EMNFSatisfaction (w/Milestone) Matching No No First Sat_Neg EMNZSatisfaction (w/Milestone) Matching No No Repeat Sat_Neg EMYFSatisfaction (w/Milestone) Matching Yes Yes First Sat_Pos EMYZSatisfaction (w/Milestone) Matching Yes Yes Repeat Sat_Pos EXNFSatisfaction (w/Milestone) Not Matching No Yes First Sat_Neg EXNZSatisfaction (w/Milestone) Not Matching No Yes Repeat Sat_Neg EXYFSatisfaction (w/Milestone) Not Matching Yes No First Sat_Neg EXYZSatisfaction (w/Milestone) Not Matching Yes No Repeat Sat_Neg OANFResolution (w/Milestone) Agent-Only No N/A First Res_Neg OANZ Resolution(w/Milestone) Agent-Only No N/A Repeat Res_Neg OAYF Resolution(w/Milestone) Agent-Only Yes N/A First Res_Neu OAYZ Resolution(w/Milestone) Agent-Only Yes N/A Repeat Res_Neu OMNF Resolution(w/Milestone) Matching No No First Res_Neg OMNZ Resolution (w/Milestone)Matching No No Repeat Res_Neg OMYF Resolution (w/Milestone) Matching YesYes First Res_Pos OMYZ Resolution (w/Milestone) Matching Yes Yes RepeatRes_Pos OXNF Resolution (w/Milestone) Not Matching No Yes First Res_NegOXNZ Resolution (w/Milestone) Not Matching No Yes Repeat Res_Neg OXYFResolution (w/Milestone) Not Matching Yes No First Res_Neg OXYZResolution (w/Milestone) Not Matching Yes No Repeat Res_Neg RANFResolution Agent-Only No N/A First Res_Neg RANZ Resolution Agent-Only NoN/A Repeat Res_Neg RAYF Resolution Agent-Only Yes N/A First Res_Neu RAYZResolution Agent-Only Yes N/A Repeat Res_Neu RMNF Resolution Matching NoNo First Res_Neg RMNZ Resolution Matching No No Repeat Res_Neg RMYFResolution Matching Yes Yes First Res_Pos RMYZ Resolution Matching YesYes Repeat Res_Pos RXNF Resolution Not Matching No Yes First Res_NeuRXNZ Resolution Not Matching No Yes Repeat Res_Neu RXYF Resolution NotMatching Yes No First Res_Neg RXYZ Resolution Not Matching Yes No RepeatRes_Neg SANF Satisfaction Agent-Only No N/A First Sat_Neg SANZSatisfaction Agent-Only No N/A Repeat Sat_Neg SAYF SatisfactionAgent-Only Yes N/A First Sat_Neu SAYZ Satisfaction Agent-Only Yes N/ARepeat Sat_Neu SMNF Satisfaction Matching No No First Sat_Neg SMNZSatisfaction Matching No No Repeat Sat_Neg SMYF Satisfaction MatchingYes Yes First Sat_Pos SMYZ Satisfaction Matching Yes Yes Repeat Sat_PosSXNF Satisfaction Not Matching No Yes First Sat_Neu SXNZ SatisfactionNot Matching No Yes Repeat Sat_Neu SXYF Satisfaction Not Matching Yes NoFirst Sat_Neg SXYZ Satisfaction Not Matching Yes No Repeat Sat_Neg FXFXNone Flagged Contact N/A N/A N/A N/A DXDX None Dropped Contact N/A N/AN/A N/A TXTA None Escalation N/A N/A N/A N/A TXTD None Transfer N/A N/AN/A N/A

Each Response Code may be assigned a priority indicating the level oflikelihood that error in agent inference of customer perception hasoccurred. These priorities become part of an algorithm used by theperformance management software to present records for evaluation by theQuality Assurance team. Table 7 below sets forth an exemplary list ofpriorities.

TABLE 7 Response Code Priorities PR CODE SURVEY ALIGNMENT AGENT CUSTREPEAT CLUSTER 1 EXYZ Satisfaction (w/Milestone) Not Matching Yes NoRepeat Sat_Neg 2 EXYF Satisfaction (w/Milestone) Not Matching Yes NoFirst Sat_Neg 3 EMNZ Satisfaction (w/Milestone) Matching No No RepeatSat_Neg 4 EMNF Satisfaction (w/Milestone) Matching No No First Sat_Neg 5EANZ Satisfaction (w/Milestone) Agent-Only No N/A Repeat Sat_Neg 6 EANFSatisfaction (w/Milestone) Agent-Only No N/A First Sat_Neg 7 EXNZSatisfaction (w/Milestone) Not Matching No Yes Repeat Sat_Neg 8 EXNFSatisfaction (w/Milestone) Not Matching No Yes First Sat_Neg 9 OXYZResolution (w/Milestone) Not Matching Yes No Repeat Res_Neg 10 OXYFResolution (w/Milestone) Not Matching Yes No First Res_Neg 11 OMNZResolution (w/Milestone) Matching No No Repeat Res_Neg 12 OMNFResolution (w/Milestone) Matching No No First Res_Neg 13 OANZ Resolution(w/Milestone) Agent-Only No N/A Repeat Res_Neg 14 OANF Resolution(w/Milestone) Agent-Only No N/A First Res_Neg 15 OXNZ Resolution(w/Milestone) Not Matching No Yes Repeat Res_Neg 16 OXNF Resolution(w/Milestone) Not Matching No Yes First Res_Neg 17 RXYZ Resolution NotMatching Yes No Repeat Res_Neg 18 SXYZ Satisfaction Not Matching Yes NoRepeat Sat_Neg 19 RXYF Resolution Not Matching Yes No First Res_Neg 20SXYF Satisfaction Not Matching Yes No First Sat_Neg 21 RMNZ ResolutionMatching No No Repeat Res_Neg 22 SMNZ Satisfaction Matching No No RepeatSat_Neg 23 RMNF Resolution Matching No No First Res_Neg 24 SMNFSatisfaction Matching No No First Sat_Neg 25 RANZ Resolution Agent-OnlyNo N/A Repeat Res_Neg 26 SANZ Satisfaction Agent-Only No N/A RepeatSat_Neg 27 RANF Resolution Agent-Only No N/A First Res_Neg 28 SANFSatisfaction Agent-Only No N/A First Sat_Neg 29 EAYZ Satisfaction(w/Milestone) Agent-Only Yes N/A Repeat Sat_Neu 30 EAYF Satisfaction(w/Milestone) Agent-Only Yes N/A First Sat_Neu 31 OAYZ Resolution(w/Milestone) Agent-Only Yes N/A Repeat Res_Neu 32 OAYF Resolution(w/Milestone) Agent-Only Yes N/A First Res_Neu 33 RXNZ Resolution NotMatching No Yes Repeat Res_Neu 34 SXNZ Satisfaction Not Matching No YesRepeat Sat_Neu 35 RXNF Resolution Not Matching No Yes First Res_Neu 36SXNF Satisfaction Not Matching No Yes First Sat_Neu 37 RAYZ ResolutionAgent-Only Yes N/A Repeat Res_Neu 38 SAYZ Satisfaction Agent-Only YesN/A Repeat Sat_Neu 39 RAYF Resolution Agent-Only Yes N/A First Res_Neu40 SAYF Satisfaction Agent-Only Yes N/A First Sat_Neu 41 OMYZ Resolution(w/Milestone) Matching Yes Yes Repeat Res_Pos 42 OMYF Resolution(w/Milestone) Matching Yes Yes First Res_Pos 43 EMYZ Satisfaction(w/Milestone) Matching Yes Yes Repeat Sat_Pos 44 EMYF Satisfaction(w/Milestone) Matching Yes Yes First Sat_Pos 45 RMYZ Resolution MatchingYes Yes Repeat Res_Pos 46 RMYF Resolution Matching Yes Yes First Res_Pos47 SMYZ Satisfaction Matching Yes Yes Repeat Sat_Pos 48 SMYFSatisfaction Matching Yes Yes First Sat_Pos

Response Codes may be used for two primary purposes. The first purposeis to prioritize the various combinations of agent-customer surveyresponses for review. Those that are incongruent and involve repeatcalls are higher priority, while those that are congruent with bothparties responding favorably are lower priority. The second purpose isfor ease in communication in various screens and reports of theperformance management software. The purpose and usage of such responsecodes are set forth in Table 8 below.

TABLE 8 Response Code Usage PURPOSE USAGE Prioritization Response Codesindicate congruency between agent-customer survey responses, the surveyquestion responded to and the whether or not the call was a repeat forthe same concern. Calls that are assigned a higher priority are morelikely to be evaluated by the Quality Assurance team. The guidelines forestablishing priorities are: If the agent indicates that a customer wassatisfied and that their issue was resolved, and the customer indicatesthe opposite, and it is a repeat call, the chances of identifying anerror and creating a rich coaching opportunity are very high If both theagent and customer respond favorably to the satisfaction and/orresolution survey questions, chances are high that everything was donecorrectly. However, these records are reviewed to ensure that the agentadhered to policy Evaluation Screen Response Codes appear in the toppanel of the evaluation screen so that the QA Analyst is aware of thecondition of survey responses Task Screen When conducting coaching andcounseling sessions with the agent, the Task screen displays theResponse Code for the record being reviewed. This allows the agent andthe supervisor to better understand the purpose of the coaching orcounseling session. Reporting Various reports generated illustrateResponse Codes for the primary purpose of identifying trends

As noted above, Response Codes are generated after the agent completesthe Agent Survey and after the customer either completes the CustomerSurvey, or has had the opportunity to complete the Customer Survey butdid not. Agent Surveys may be presented to Data Assurance for evaluationin order of priority assigned to each Response Code. A more detaileddescription in order of priority, and the prime indicators associatedwith each Response Code is set forth in Table 9 below. It should benoted, however, that “prime indicators” are not inclusive of everypotential root cause. Rather, they may be used as a guideline related tothe generation of a Response Code.

TABLE 9 Response Codes Priority Detailed Description CODE DESCRIPTIONPRIME INDICATORS 1 EXYZ Survey Question: Satisfaction An opportunityexists to coach the agent Milestone: Present with regard to engagementand etiquette Alignment: Not Matching The customer was not satisfied dueto an Agent Response: Yes existing policy or process Repeat Status:Repeat Potential concerns with the method of resolution utilized by theagent 2 EXYF Survey Question: Satisfaction An opportunity exists tocoach the agent Milestone: Present with regard to engagement andetiquette Alignment: Not Matching The customer was not satisfied due toan Agent Response: Yes existing policy or process Repeat Status: FirstPotential concerns with the method of resolution utilized by the agent 3EMNZ Survey Question: Satisfaction The customer was not satisfied due toan Milestone: Present existing policy or process Alignment: Matching Theagent is requesting help related to call Agent Response: No handlingRepeat Status: Repeat 4 EMNF Survey Question: Satisfaction The customerwas not satisfied due to an Milestone: Present existing policy orprocess Alignment: Matching The agent is requesting help related to callAgent Response: No handling Repeat Status: First 5 EANZ Survey Question:Satisfaction The agent is serving as a reliable proxy for Milestone:Present the customer Alignment: Agent-Only The customer was notsatisfied due to an Agent Response: No existing policy or process RepeatStatus: Repeat The agent is asking for help related to call handling 6EANF Survey Question: Satisfaction The agent is serving as a reliableproxy for Milestone: Present the customer Alignment: Agent-Only Thecustomer was not satisfied due to an Agent Response: No existing policyor process Repeat Status: First The agent is asking for help related tocall handling 7 EXNZ Survey Question: Satisfaction Agent error ininference of customer Milestone: Present perception Alignment: NotMatching The agent is asking for help related to call Agent Response: Nohandling Repeat Status: Repeat 8 EXNF Survey Question: SatisfactionAgent error in inference of customer Milestone: Present perceptionAlignment: Not Matching The agent is asking for help related to callAgent Response: No handling Repeat Status: First 9 OXYZ Survey Question:Resolution Concern with the method of resolution Milestone: Presentutilized by an individual agent Alignment: Not Matching Training concernaffecting multiple agents Agent Response: Yes Problem with fulfillment(etc.) which Repeat Status: Repeat occurred outside the control of thesupport organization 10 OXYF Survey Question: Resolution Concern withthe method of resolution Milestone: Present utilized by an individualagent Alignment: Not Matching Training concern affecting multiple agentsAgent Response: Yes Problem with fulfillment (etc.) which Repeat Status:First occurred outside the control of the support organization 11 OMNZSurvey Question: Resolution Potential concern with existing policy orMilestone: Present process Alignment: Matching Training concernaffecting an individual Agent Response: No agent or group of agentsRepeat Status: Repeat 12 OMNF Survey Question: Resolution Potentialconcern with existing policy or Milestone: Present process Alignment:Matching Training concern affecting an individual Agent Response: Noagent or group of agents Repeat Status: First 13 OANZ Survey Question:Resolution Agent error in inference of customer Milestone: Presentperception Alignment: Agent-Only Potential concern with existing policyor Agent Response: No process Repeat Status: Repeat Training concernaffecting an individual agent or group of agents 14 OANF SurveyQuestion: Resolution Agent error in inference of customer Milestone:Present perception Alignment: Agent-Only Potential concern with existingpolicy or Agent Response: No process Repeat Status: First Trainingconcern affecting an individual agent or group of agents 15 OXNZ SurveyQuestion: Resolution Agent error in inference of customer Milestone:Present perception Alignment: Not Matching Agent Response: No RepeatStatus: Repeat 16 OXNF Survey Question: Resolution Agent error ininference of customer Milestone: Present perception Alignment: NotMatching Agent Response: No Repeat Status: First 17 RXYZ SurveyQuestion: Resolution Concern with the method of resolution Milestone:Not Present utilized by an individual agent Alignment: Not MatchingTraining concern affecting multiple agents Agent Response: Yes RepeatStatus: Repeat 18 SXYZ Survey Question: Satisfaction An opportunityexists to coach the agent Milestone: Not Present with regard toengagement and etiquette Alignment: Not Matching The customer was notsatisfied due to an Agent Response: Yes existing policy or processRepeat Status: Repeat 19 RXYF Survey Question: Resolution Concern withthe method of resolution Milestone: Not Present utilized by anindividual agent Alignment: Not Matching Training concern affectingmultiple agents Agent Response: Yes Repeat Status: First 20 SXYF SurveyQuestion: Satisfaction An opportunity exists to coach the agentMilestone: Not Present with regard to engagement and etiquetteAlignment: Not Matching The customer was not satisfied due to an AgentResponse: Yes existing policy or process Repeat Status: First 21 RMNZSurvey Question: Resolution Potential concern with existing policy orMilestone: Not Present process Alignment: Matching Training concernaffecting an individual Agent Response: No agent or group of agentsRepeat Status: Repeat 22 SMNZ Survey Question: Satisfaction Anopportunity exists to coach the agent Milestone: Not Present with regardto engagement and etiquette Alignment: Matching The customer was notsatisfied due to an Agent Response: No existing policy or process RepeatStatus: Repeat 23 RMNF Survey Question: Resolution Potential concernwith existing policy or Milestone: Not Present process Alignment:Matching Training concern affecting an individual Agent Response: Noagent or group of agents Repeat Status: First 24 SMNF Survey Question:Satisfaction An opportunity exists to coach the agent Milestone: NotPresent with regard to engagement and etiquette Alignment: Matching Thecustomer was not satisfied due to an Agent Response: No existing policyor process Repeat Status: First 25 RANZ Survey Question: Resolution Theagent is serving as a reliable proxy for Milestone: Not Present thecustomer Alignment: Agent-Only The agent is requesting help related tocall Agent Response: No handling Repeat Status: Repeat 26 SANZ SurveyQuestion: Satisfaction The agent is serving as a reliable proxy forMilestone: Not Present the customer Alignment: Agent-Only The customerwas not satisfied due to an Agent Response: No existing policy orprocess Repeat Status: Repeat The agent is asking for help related tocall handling 27 RANF Survey Question: Resolution The agent is servingas a reliable proxy for Milestone: Not Present the customer Alignment:Agent-Only The agent is requesting help related to call Agent Response:No handling Repeat Status: First 28 SANF Survey Question: SatisfactionThe agent is serving as a reliable proxy for Milestone: Not Present thecustomer Alignment: Agent-Only The customer was not satisfied due to anAgent Response: No existing policy or process Repeat Status: First Theagent is asking for help related to call handling 29 EAYZ SurveyQuestion: Satisfaction The customer was satisfied with the serviceMilestone: Present received Alignment: Agent-Only Data Assurance shouldvalidate satisfaction Agent Response: Yes and policy/process adherenceRepeat Status: Repeat 30 EAYF Survey Question: Satisfaction The customerwas satisfied with the service Milestone: Present received Alignment:Agent-Only Data Assurance should validate satisfaction Agent Response:Yes and policy/process adherence Repeat Status: First 31 OAYZ SurveyQuestion: Resolution The customer believes the issue was Milestone:Present resolved correctly Alignment: Agent-Only Data Assurance shouldvalidate resolution Agent Response: Yes method and policy/processadherence Repeat Status: Repeat 32 OAYF Survey Question: Resolution Thecustomer believes the issue was Milestone: Present resolved correctlyAlignment: Agent-Only Data Assurance should validate resolution AgentResponse: Yes method and policy/process adherence Repeat Status: First33 RXNZ Survey Question: Resolution Agent error in inference of customerMilestone: Not Present perception Alignment: Not Matching Data Assuranceshould validate resolution Agent Response: No method and policy/processadherence Repeat Status: Repeat 34 SXNZ Survey Question: SatisfactionAgent error in inference of customer Milestone: Not Present perceptionAlignment: Not Matching Data Assurance should validate satisfactionAgent Response: No and policy/process adherence Repeat Status: Repeat 35RXNF Survey Question: Resolution Agent error in inference of customerMilestone: Not Present perception Alignment: Not Matching Data Assuranceshould validate resolution Agent Response: No method and policy/processadherence Repeat Status: First 36 SXNF Survey Question: SatisfactionAgent error in inference of customer Milestone: Not Present perceptionAlignment: Not Matching Data Assurance should validate satisfactionAgent Response: No and policy/process adherence Repeat Status: First 37RAYZ Survey Question: Resolution The customer believes the issue wasMilestone: Not Present resolved correctly Alignment: Agent-Only DataAssurance should validate resolution Agent Response: Yes method andpolicy/process adherence Repeat Status: Repeat 38 SAYZ Survey Question:Resolution The customer was satisfied with the service Milestone: NotPresent received Alignment: Agent-Only Data Assurance should validatesatisfaction Agent Response: Yes and policy/process adherence RepeatStatus: Repeat 39 RAYF Survey Question: Resolution The customer believesthe issue was Milestone: Not Present resolved correctly Alignment:Agent-Only Data Assurance should validate resolution Agent Response: Yesmethod and policy/process adherence Repeat Status: First 40 SAYF SurveyQuestion: Satisfaction The customer was satisfied with the serviceMilestone: Not Present received Alignment: Agent Only Data Assuranceshould validate satisfaction Agent Response: Yes and policy/processadherence Repeat Status: First 41 OMYZ Survey Question: Resolution Verystrong likelihood that the issue was Milestone: Present resolvedAlignment: Matching Data Assurance should validate resolution AgentResponse: Yes and policy/process adherence Repeat Status: Repeat 42 OMYFSurvey Question: Resolution Very strong likelihood that the issue wasMilestone: Present resolved Alignment: Matching Data Assurance shouldvalidate resolution Agent Response: Yes and policy/process RepeatStatus: First 43 EMYZ Survey Question: Satisfaction Very stronglikelihood that the customer Milestone: Present was satisfied Alignment:Matching Data Assurance should validate satisfaction Agent Response: Yesand policy/process adherence Repeat Status: Repeat 44 EMYF SurveyQuestion: Satisfaction Very strong likelihood that the customerMilestone: Present was satisfied Alignment: Matching Data Assuranceshould validate satisfaction Agent Response: Yes and policy/processadherence Repeat Status: First 45 RMYZ Survey Question: Resolution Verystrong likelihood that the issue was Milestone: Not Present resolvedAlignment: Matching Data Assurance should validate resolution AgentResponse: Yes and policy/process Repeat Status: Repeat 46 RMYF SurveyQuestion: Resolution Very strong likelihood that the issue wasMilestone: Not Present resolved Alignment: Matching Data Assuranceshould validate resolution Agent Response: Yes and policy/process RepeatStatus: First 47 SMYZ Survey Question: Satisfaction Very stronglikelihood that the customer Milestone: Not Present was satisfiedAlignment: Matching Data Assurance should validate satisfaction AgentResponse: Yes and policy/process adherence Repeat Status: Repeat 48 SMYFSurvey Question: Satisfaction Very strong likelihood that the customerMilestone: Not Present was satisfied Alignment: Matching Data Assuranceshould validate satisfaction Agent Response: Yes and policy/processadherence Repeat Status: First

Referring now to FIG. 3, there is shown a balanced service process 208utilizing Zacoustic performance management software 300 according to anembodiment of the present invention. An customer contact point andcustomer calibrator 302 provides that for every call handled, thecustomer contact point predict how customers are going to respond toexisting survey questions. Zacoustic does not replace survey questionscurrently in use by a client; rather it fills the gap left by 85-95% ofunresponsive customers. Utilize the client's existing survey questionsand venue, the responses are fed through an API 410 to Zacousticdatabase 416 (see FIG. 4). The survey is imbedded into the client's CRM,and there is no impact to average handle time (AHT). Moreover, there isno personally-identifiable information (PII) or payment card industry(PCI) data transmitted. Agent-required completion of the predictivesurvey does not contribute to AHT increase; rather AHT is loweredthrough exposed best practice.

When actual customer survey responses are received, they are compared toagent predictions for that call. The Match Rate metric is based onaccurate agent predictions (e.g., Matched Responses/Total MatchOpportunities=Match Rate). As the Match Rate improves, agents becomemore aware of customer sentiment and are more likely to take steps todeliver improved CX. For example, agents start at about 40%, and improveto about 90% within four weeks. As agents begin to understand that theyare not self-evaluating, rather predicting, the accuracy of theirpredictions improve. As agents demonstrate sustained accuratepredictions, Zacoustic trusts their data just as though it came from thecustomer. Zacoustic algorithm only trusts agent-generated data aftersustained accurate predictions (i.e., Match Rate) are demonstrated bythe agent. This fills the survey gap generating statistically sound 100%customer feedback using the agent as a reliable customer proxy.

It should be noted at this juncture that this calibration process may beused not only with the human agents 228 and human supervisors 232, butalso with BOTs, Chat BOTs, etc. 210 coupled to the BSP 208.

Attributes of every agent prediction—call disposition and AHT may beauto-populated—enabling complex CX big data. Other factors such ascustomer experience score, issue resolution score, repeat call status,net promoter scores, etc. may also be used. With prior art approaches,QA randomly selects calls, the average FCR is 70%, and resolved callsare often evaluated. With the Zacoustic approach described herein,good/bad calls are separated, calls which have not been resolved areautomatically sent to QA, resulting in a great improvement to CX. Itremoves denial from agent-thinking with regard to candid feedback; whenagents predict unfavorable responses, they are open to coaching. Asshown in Table 10 below, the addition of agent-calibrated CX and FCRdata alongside AHT for every call, by agent and call driver is anindustry first and exposes biggest pain points and best practices.

TABLE 10 Zacoustic Reporting Call Driver: Registration Calls AHT CX FCRTotal Queue Performance 9,952 11:12 44% 28% Agent: Janet Lane 327  6:4488% 74%

Referring again to FIG. 4, there is shown a flowchart for maximizingfirst contact resolution according to one embodiment of the presentinvention. The top portion illustrates a client's CRM system runningZendesk 402 with a form 404, which may include for example ticket ID,agent ID, state, call type, and times. It may also include an agentwebform 406 and an agent predictive survey 408 (an enlarged sample whichmay be seen in FIG. 14). It may also be running SurveyPal (a datacapture software which may be integrated with CECs such as Salesforce,Zendesk, or ServiceNow as shown in FIG. 1) 412 with a form 414, whichmay include for example a SurveyPal customer survey and a ticket ID.Each of the aforementioned elements may be running on a computer system418. The bottom portion illustrates Zacoustic components, including anAPI 410 connected to receive inputs from the forms 404, 408, and 414,and collect them for processing and storage by Zacoustic database 416. AZacoustic client 420 is also coupled to run on the client's computersystem 418.

Referring now to FIGS. 5A and 5B, there is shown a balanced serviceprocess according to another embodiment of the present invention forresponding to an email contact. A customer email may be received at step502. At step 504, a determination is made whether the issue noted in theemail has been resolved. If not, a response is sent at step 506. If theissue was resolved, it is determined as solved at step 512, and acustomer survey is sent at step 514. At step 508, it is determinedwhether a response has been received. If not, it is presumed solvedafter 7 days at step 510. If so, it is determined as solved at step 512,and a customer survey is sent at step 514. The agent in either casepredicts the outcomes at step 516 with the predictive survey 408 (FIG. 4and FIG. 14).

The process continues with step 518 of FIG. 5B to determine whether thecustomer has responded to the survey. If not, the process ends at step520. If the customer has responded, Zacoustic compares the predictivesurvey with the customer response at step 522. At step 524, adetermination is made whether the responses match. If not, calibrationcoaching is automatically implemented at step 526. If they do match, theprocess ends at step 528.

Referring now to FIG. 6, a balanced service process according to anotherembodiment of the present invention is shown for responding to a phonecall. An outbound call is made at step 602, and the issue is determinedas resolved at step 604 by Zendesk, for example. A customer survey issent at step 606 at essentially the same time that the agent predictionis made at step 608. A determination is made at step 610 whether thecustomer responds. If not, the process ends at step 612. If so,Zacoustic compares the responses at 614, and a determination is madewhether the responses match at step 616. If not, calibration coaching isautomatically implemented at step 618. If they do match, the processends at step 620.

Referring now to FIGS. 7A and 7B, a balanced service process accordingto another embodiment of the present invention for responding to a chatcontact is shown. The customer may request a chat at step 702. A chatsession ensues at step 704, and the chat session is ended by thecustomer at step 706. The issue is determined as resolved at step 708 byZendesk, for example. A customer survey is sent at step 710 atessentially the same time that the agent prediction is made at step 712.As continued with FIG. 7B, a determination is made at step 714 whetherthe customer responds. If not, the process ends at step 716. If so,Zacoustic compares the responses at 718, and a determination is madewhether the responses match at step 720. If not, calibration coaching isautomatically implemented at step 722. If they do match, the processends at step 724.

Referring now to FIG. 8, a balanced service process according to anotherembodiment of the present invention for use with calibrated agentpredictions is shown. Calibrated agent predictions are input at step 802into the Zacoustic database 804. Zacoustic then identifies and separatesunsuccessful interactions at step 806 from successful interactions atstep 810. Zacoustic then categorizes the unsuccessful interactions atstep 808 utilizing cause drivers such as issue type, resolution,satisfaction, repeat call, and AHT, among others. Zacoustic alsoidentifies the successful transactions for purposes of bestpractice/recognition. Based on the factors identified in step 808, thosefactors are input to a portion of the Zacoustic database 804 at step 814into a Zacoustic QA tool. This may then, in turn, lead to changes in thecurrent QA form at step 816 and high-impact agent coaching sessions atstep 818.

Referring now to FIG. 9, a balanced service process according to anotherembodiment of the present invention for use with calibrated agentpredictions is shown. Calibrated agent predictions are input at step 902into the Zacoustic database 904. Zacoustic then identifies and separatesunsuccessful interactions at step 906 from successful interactions atstep 908. Zacoustic then categorizes the unsuccessful interactions atstep 910 utilizing cause drivers such as issue type, highest volume,lowest resolution, lowest satisfaction, and highest AHT, among others.Zacoustic also identifies the successful transactions for purposes ofproduct improvements. Based on the factors identified in step 910, thosefactors are compared with high performance agents at step 914. If not, adetermination that there may be a process problem is made at step 916.If so, those factors may be used in best practice sharing, but alsotraining and knowledge base use.

Referring now to FIG. 10, a balanced service process according toanother embodiment of the present invention including machine learningis shown. Cause drivers 1002 such as those to the left of the Zacousticdatabase 1004 may be input into the database 1004 to produce an agentpredictive survey 1006. If an actual customer 1008 responds to surveyssent to her/him, Zacoustic may compare the two, ascertaindifference/similarities, and feedback such machine learning to theZacoustic database.

Referring now to FIG. 11, a calibration dashboard for use with balancedservice process according to an embodiment of the present invention isshown. Zacoustic displays agents that are not calibrated, those that itbelieves are, and supervisors must validate those that are fullycalibrated. Zacoustic does not trust agent-generated data until both themachine and human validate calibration.

Referring now to FIG. 12, another calibration dashboard for use with thebalanced service process according to an embodiment of the presentinvention is shown. This view is for Agent Anna Goldman and can be usedfor individual coaching. Her supervisors can double click on eachindividual agent to review all agent and customer calibrationopportunities

Referring now to FIG. 13, an executive dashboard for use with thebalanced service process according to an embodiment of the presentinvention is shown, illustrating call driver vs. AHT, CX and Resolution,which allows users to quickly find the greatest pain points (allstemming from agent calibrated data).

Referring now to FIG. 14, another executive dashboard for use with thebalanced service process according to an embodiment of the presentinvention is shown. By double clicking into the data exposes thoseagent(s) that define best practice within the selected call driver. Inthis view, Agent “Wendy Barnes'” can be defined as best practice andknowledge share to other agents within the queue/KB.

While various exemplary embodiments have been described above, it shouldbe understood that they have been presented by way of example only, andnot limitation. Thus, the breadth and scope of the present inventionshould not be limited by any of the above-described exemplaryembodiments, but should instead be defined only in accordance with thefollowing claims and their equivalents.

What is claimed is:
 1. A system for customer contact management,comprising: a customer contact environment comprising a database and aplurality of agents, wherein said contact environment is coupled toreceive customer contacts from a network and present each of thecustomer contacts to one or more of said plurality of agents; a balancedservice process, comprising: an agent survey for determining andmanaging real-time, intraday, and historical resolver disposition ofcontact (RDP) and agents' belief about customers' view on contactresolution and customer satisfaction; a customer survey for determiningand managing real-time, intraday, and historical customer input/view ondisposition of contact (CDP); wherein said process for aligning theagent and the customer on each contact comprises one or more of thefollowing: a data generator for determining first contact resolution(FCR) rates and customer satisfaction (CSAT) from the results of saidagent survey and said customer survey, wherein said results are storedin said database; a processor within said database for dynamicallyreporting issues driving contact volume; a processor within saiddatabase for determining every contact that was not resolved; aprocessor within said database for assigning a plurality of responsecodes each of which is indicative of an outcome of said agent survey andsaid customer survey for each of the contacts; and a closed loop channelwithin said database to define, report and correct actions and trendingissues that impede FCR and CSAT.
 2. The system according to claim 1,wherein said issues driving contact volume comprise said real-time,intraday, and historical RDP, CDP, FCR and CSAT, and exception rates. 3.The system according to claim 1, wherein said trending issues thatimpede FCR and CSAT are based on said dynamically reported issuesdriving contact volume.
 4. The system according to claim 1, wherein saidagent is prompted with said agent survey upon completion of each saidcontact.
 5. The system according to claim 4, wherein said agent isprompted during said agent survey to answer whether the customerbelieves the issue causing each said contact was resolved or not.
 6. Thesystem according to claim 4, wherein said agent is prompted during saidagent survey to answer whether the customer for each said contact wassatisfied or not.
 7. The system according to claim 1, wherein saidcustomer is prompted with said customer survey upon completion of eachsaid contact.
 8. The system according to claim 7, wherein said customeris prompted during said customer survey to answer whether the issuecausing each said contact was resolved or not.
 9. The system accordingto claim 7, wherein said customer is prompted during said customersurvey to answer whether the customer for each said contact wassatisfied or not.
 10. The system according to claim 1, wherein saidresponse codes are generated after said agent completes said agentsurvey and after said customer either completes said customer survey, orhas had the opportunity to complete said customer survey but did not.11. The system according to claim 1, wherein said response codes areprioritized.
 12. The system according to claim 11, wherein said responsecodes are indicative of one or more of congruency between agent-customersurvey responses, the survey question responded to and, whether or notthe call was a repeat for the same concern.
 13. The system according toclaim 1, wherein said contact environment further comprises a chat bot.14. The system according to claim 13, wherein said chat bot is coupledto said database to store data input through the chat bot by thecustomer and data output by the chat bot to the customer.
 15. The systemaccording to claim 14, wherein said balanced service process furthercomprises a bot coupled to said database.
 16. The system according toclaim 15, wherein said bot is adapted to be calibrated by the datagenerated in said balanced service process.
 17. The system according toclaim 16, wherein each said agent may be calibrated by the datagenerated in said balanced service process.
 18. The system according toclaim 16, wherein said calibrated bot may prompt each said agent. 19.The system according to claim 16, wherein said calibrated bot is adaptedfor machine learning based on the data generated in said balance serviceprocess and stored in said database.
 20. The system according to claim16, wherein said calibrated bot may generate a unique customer surveyfor each unique customer contact.